In this chapter, we use two urban indicators to examine intra-urban inequalities in the municipality of São Paulo, Brazil: the Human Development Index (HDI), from the United Nations Development Program, and the Economic Concentration Index (ECI), proposed in this study. Using district-level data, we apply Exploratory Spatial Data Analysis (ESDA) methods that account for spatial effects, that is, spatial autocorrelation and spatial heterogeneity. Spatial autocorrelation occurs when value similarity and locational similarity coincide. Spatial heterogeneity exists when structural changes related to location are detected in the data set, and spatial regimes may be present. We show that spatial autocorrelation and spatial heterogeneity are detected in the spatial distribution of HDI and ECI in São Paulo Municipality, and therefore intra-urban inequalities exist with respect to both urban indicators. The development level varies substantially across districts, and center and periphery are the most obvious spatial regimes characterizing this variation. The ESDA methods described in this study can be adopted by planners to examine different variables, leading to more reliable results based on statistical tests and revealing, more precisely, locations that require more/less attention.
Keywords
- Gross Domestic Product
- Geographic Information System
- Spatial Autocorrelation
- Human Development Index
- Positive Spatial Autocorrelation
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Haddad, M.A. (2009). Examining the Spatial Distribution of Urban Indicators in São Paulo, Brazil. In: Sirgy, M.J., Phillips, R., Rahtz, D.R. (eds) Community Quality-of-Life Indicators: Best Cases III. Community Quality-of Life Indicators, vol 1. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2257-8_5
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